Amey Band – Medium

Published in Towards Data Science

·Pinned

Multi-class Classification — One-vs-All & One-vs-One

Multi-class classification is the classification technique that allows us to categorize the test data into multiple class labels present in — Introduction There are primarily three types of machine learning: Supervised Unsupervised Reinforcement Supervised machine learning categorizes into regression and classification. We use the regression technique to predict the target values of continuous variables, like predicting the salary of an employee. In contrast, we use the classification technique for predicting the class labels for given input data.

Multiclass Classification

6 min read

Published in Towards Data Science

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How to find the optimal value of K in KNN?

Visualize error rate vs. K plot to find the most suitable K value. — Introduction K-Nearest Neighbors is the supervised machine learning algorithm used for classification and regression. It manipulates the training data and classifies the new test data based on distance metrics. It finds the k-nearest neighbors to the test data, and then classification is performed by the majority of class labels.

Data Science

6 min read

How to find the optimal value of K in KNN?

Published in Towards Data Science

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Textfeatures: Library for extracting basic features from text data

This is a python package that helps you to extract the basic features from the text data such as hashtags, stopwords, numerics which will… — Introduction: textfeatures When we handle text data, we always have concerns about the data features, pre-processing of data, and more likely the predictions. To improve our model, it is important to understand the data and find the more interesting features in the data like hashtags, links, and many more.

Machine Learing

5 min read

Textfeatures: Library for extracting basic features from text data

Published in Towards Data Science

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Data Science Model Building Life Cycle

Introduction — Introduction When we come across a business analytical problem, without acknowledging the stumbling blocks, we proceed towards the execution. Before realizing the misfortunes, we try to implement and predict the outcomes. But do those outcomes reveal the strategies to decode the problems? The answer is NO. We can’t come up with…

Data Science

7 min read

Published in Plus Marketing

·Nov 5, 2020

Don’t Sell Your Emotions on Social Media

Don’t ruin your personnel life looking at fake perfection or social comparison on social media. — Before reading the article, I would like it if you take some time and think about the changes in your social and professional behavior since you have started using social media. Have you got anything? No! Don’t worry. Take a long breath and start reading the article. “THE TECHNOLOGY THAT CONNECTS…

Social Media

7 min read

Published in The Startup

·Sep 23, 2020

Introduction to CNN & Image Classification Using CNN in PyTorch

Design your first CNN architecture using Fashion MNIST dataset. — Introduction Image Classification is the technique to extract the features from the images to categorize them in the defined classes. It is a common-sense problem for the human to identify the images but, for the machine, it’s definitely not. …

Data Science

7 min read

Introduction to CNN & Image Classification Using CNN in PyTorch

Sep 21, 2020

The default of Credit Card Clients Dataset: Classification & Evaluation

Introduction — Introduction Let’s come directly on the point, in this article, we will try to develop a machine model on “Default of Credit Card Clients Dataset” hosted on Kaggle and precut whether a customer will default the payment next month. Dataset Information This dataset contains information on default payments, demographic factors, credit data, history…

Machine Learning

8 min read

Default of Credit Card Clients Dataset: Classification & Evaluation

Published in Towards Data Science

·Sep 14, 2020

Text2emotion: Python package to detect emotions from textual data

This package will help you to discover the emotions in textual messages. — Introduction Emotion is the state of mind that is aligned with feelings, and thoughts usually directed toward a specific object. Emotion is a behavior that reflects personal significance or opinion regarding the interaction we have with other human beings or related to a certain event. The human being is able to…

Data Science

5 min read

Text2emotion: Python package to detect emotions from textual data

Published in Python in Plain English

·May 6, 2020

Twitter Sentiment Analysis using Vader & Tweepy

Introduction — Introduction Whenever a user wants to share his opinion regarding any trending topic on social media, we try to find the sentiment score of that expressed opinion using sentiment analysis. Twitter is the most widely used micro-blogging social media platform, having nearly 145 million daily active users. …

Sentimental Analysis

10 min read

Twitter Sentiment Analysis using Vader & Tweepy

Published in The Startup

·May 4, 2020

Beginner’s guide to build Recommendation Engine in Python

Introduction — Introduction A while ago whenever we bought a specific product, it was probably recommended by our friends or trusted persons. But now the scenario has changed, what the product recommendations on amazon or movie recommendations on Netflix we are getting that are basically on our own interests. By analyzing the customer’s…

Machine Learning

12 min read

Beginner’s guide to build Recommendation System